fix(vector): don't inflate qdrant-error metric on embed drops (#893 r3)
Round-3 review on PR #893: - record_qdrant_operation("upsert","error") now fires only when the exhausted retry was actually a Qdrant failure (reason=="qdrant"); an embed/connection failure exhausts retries before Qdrant is called, so attributing it to mcp_qdrant_operations_total{error} inflated that signal. The cause is still captured by record_ingest_dropped. - Add test_mistral_embed_retries_on_5xx: exercises the full Mistral retry path (5xx SDKError then success), not just the predicate. - Add test_generate_does_not_retry_on_bad_request: generate() fast-fails on a permanent 4xx. - Move astrolabe_vector_ingest_dropped_total's definition into the astrolabe_ pipeline-metrics block (was in the mcp_ section). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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co-authored by
Claude Opus 4.8
parent
8f7a8432f5
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c4b6d4a017
@@ -161,18 +161,6 @@ vector_sync_processing_duration_seconds = Histogram(
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buckets=(0.1, 0.5, 1.0, 2.5, 5.0, 10.0, 30.0, 60.0),
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)
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# Documents dropped after exhausting in-process indexing retries (the scanner
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# re-picks them on a later full scan, so this is "dropped for this cycle", not
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# "lost forever"). Labelled by classified cause so the embed-drop rate from a
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# transient backend-pod rollover (connection/timeout) is alertable distinctly
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# from a persistent fault (card 309). astrolabe_ prefix: pipeline metric.
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vector_ingest_dropped_total = Counter(
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"astrolabe_vector_ingest_dropped_total",
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"Documents dropped after exhausting indexing retries, by cause",
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# reason: connection | timeout | rate_limit | server | qdrant | other
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["reason"],
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)
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vector_sync_queue_size = Gauge(
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"mcp_vector_sync_queue_size",
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"Current number of documents in processing queue",
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@@ -284,6 +272,18 @@ document_parse_failed_total = Counter(
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["reason"], # reason: timeout | oom | error
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)
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# Documents dropped after exhausting in-process indexing retries (the scanner
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# re-picks them on a later full scan, so this is "dropped for this cycle", not
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# "lost forever"). Labelled by classified cause so the embed-drop rate from a
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# transient backend-pod rollover (connection/timeout) is alertable distinctly
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# from a persistent fault (card 309).
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vector_ingest_dropped_total = Counter(
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"astrolabe_vector_ingest_dropped_total",
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"Documents dropped after exhausting indexing retries, by cause",
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# reason: connection | timeout | rate_limit | server | qdrant | other
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["reason"],
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)
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# --- Tier-0 classifier (shadow mode) -----------------------------------------
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#
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# The classifier runs a cheap pre-pass per PDF and recommends a starting tier.
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@@ -528,14 +528,17 @@ async def process_document(
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"drop_reason": reason,
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},
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)
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# Record the failed Qdrant upsert. The processing-error
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# metric is recorded once by the outer handler below, so
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# exhausted-retry failures aren't double-counted. The
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# drop counter is labelled by cause so a transient
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# rollover (connection/timeout) is alertable distinctly.
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# The document is NOT marked failed, so the next scan
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# re-picks it (re-queue via the scan loop, card 309).
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record_qdrant_operation("upsert", "error")
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# Count a failed Qdrant upsert ONLY when Qdrant was the
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# failing component; an embed/connection failure exhausts
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# retries before Qdrant is ever called, so attributing it
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# to mcp_qdrant_operations_total{error} would inflate that
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# signal. The cause is captured by record_ingest_dropped
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# instead, and the processing-error metric is recorded
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# once by the outer handler below (no double-count). The
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# document is NOT marked failed, so the next scan re-picks
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# it (re-queue via the scan loop, card 309).
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if reason == "qdrant":
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record_qdrant_operation("upsert", "error")
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record_ingest_dropped(reason)
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raise
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@@ -332,3 +332,24 @@ def test_mistral_is_transient_predicate():
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assert _is_transient(err_400) is False # permanent client error
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# ValueError has no status_code attr → getattr returns None → False.
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assert _is_transient(ValueError()) is False
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@pytest.mark.unit
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async def test_mistral_embed_retries_on_5xx(mock_mistral_client, monkeypatch):
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"""A 5xx SDKError is retried end-to-end (not just classified by the predicate)."""
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from nextcloud_mcp_server.providers import _retry
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monkeypatch.setattr(_retry.anyio, "sleep", AsyncMock(return_value=None))
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# Real SDKError instance (so `except SDKError` catches it) with a 5xx status.
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err = SDKError.__new__(SDKError)
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err.status_code = 500
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mock_mistral_client.embeddings.create_async = AsyncMock(
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side_effect=[err, _make_response([[0.1, 0.2, 0.3]])]
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)
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provider = MistralProvider(api_key="test-key", embedding_model="mistral-embed")
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embedding = await provider.embed("hello")
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assert embedding == [0.1, 0.2, 0.3]
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assert mock_mistral_client.embeddings.create_async.await_count == 2
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@@ -457,3 +457,25 @@ async def test_generate_retries_on_connection_error(mock_openai_client, monkeypa
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text = await provider.generate("prompt")
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assert text == "Generated response"
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assert create.await_count == 2
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@pytest.mark.unit
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async def test_generate_does_not_retry_on_bad_request(mock_openai_client, monkeypatch):
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"""generate() fast-fails (no retry) on a permanent 4xx."""
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import httpx
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from openai import BadRequestError
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from nextcloud_mcp_server.providers import _retry
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monkeypatch.setattr(_retry.anyio, "sleep", AsyncMock(return_value=None))
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err = BadRequestError(
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"bad", response=httpx.Response(400, request=_req()), body=None
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)
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create = AsyncMock(side_effect=err)
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mock_openai_client.chat.completions.create = create
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provider = OpenAIProvider(api_key="test-key", generation_model="gpt-4o-mini")
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with pytest.raises(BadRequestError):
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await provider.generate("prompt")
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assert create.await_count == 1 # no retry on a permanent 4xx
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